Overview

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The time-series line in the heading above is derived from current incidence cases of COVID-19 in Australia.

Column

Overview

Contributors

These graphics are licensed with a CC BY-NC-SA License

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Users must provide personal and institutional acknowledgement on reuse

In turn, we acknowledge RECON, and EuroCDC

Project has been led by Timothy Churches, Nicholas Tierney, with thanks to Stuart Lee, Dianne Cook, and Miles McBain

Visualisations and analysis made available in the covidrecon package

Source code for this visualisation are available at covid-flexdashboard

Technical Details

Analysis used includes:

  • Use

Packages used include:

  • flexdashboard
  • tidyverse
  • readr
  • tibble
  • dplyr
  • tidyr
  • stringr
  • lubridate
  • magrittr
  • countrycode
  • janitor
  • stats
  • scales
  • readxl
  • httr
  • glue
  • purrr
  • rlang
  • ggplot2
  • EpiEstim
  • changepoint
  • ggrepel
  • vctrs
  • memoise

Incidence

Column

Explanation

Cumulative Incidence for selected countries

Australian incidence

Australian incidence (semi-log)

National-level \(R_{t}\)

Column

Explanation

Selected Countries

Per Country

\(R_{t}\) for NSW

Explanation

NSW – locally-acquired & overseas-acquired cases treated separately
(cases under investigation excluded)
parametric serial interval distribution

Commentary

NSW – locally-acquired & overseas-acquired cases treated separately
(cases under investigation excluded)
serial interval distribution estimated from data

Commentary

NSW – adjusting for potential under-ascertainment, locally-acquired & overseas-acquired cases treated separately, (cases under investigation excluded), parametric serial interval distribution

In these plots, the counts of incident cases with presumed local sources of infection have been inflated by a factor of 10, and the counts of cases with presumed overseas sources of infection inflated by a factor of 1.5. This mimics ten-fold under-ascertainment of locally-transmitted cases, and 50% under-ascertainment of inbound cases.

NSW – adjusting for potential under-ascertainment, locally-acquired & overseas-acquired cases treated separately, (cases under investigation excluded), serial interval distribution estimated from data

In these plots, the counts of incident cases with presumed local sources of infection have been inflated by a factor of 10, and the counts of cases with presumed overseas sources of infection inflated by a factor of 1.5. This mimics ten-fold under-ascertainment of locally-transmitted cases, and 50% under-ascertainment of inbound cases.

NSW – locally-acquired & overseas-acquired cases treated separately
(cases under investigation included)
parametric serial interval distribution

Commentary

NSW – locally-acquired & overseas-acquired cases treated separately
(cases under investigation included)
serial interval distribution estimated from data

Commentary

NSW – all cases treated as locally-acquired
parametric serial interval distribution

From data commentary blah blah blah.

NSW – all cases treated as locally-acquired
serial interval distribution estimated from data

From data commentary blah blah blah.